refactor(mm): add CheckpointConfigBase for all ckpt models

invokeai/app/services/model_install/model_install_default.py

@@ -24,6 +24,7 @@ from invokeai.app.util.misc import uuid_string
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
+    CheckpointConfigBase,
     InvalidModelConfigException,
     ModelRepoVariant,
     ModelType,
@@ -532,7 +533,8 @@ class ModelInstallService(ModelInstallServiceBase):
     ) -> str:
         # Note that we may be passed a pre-populated AnyModelConfig object,
         # in which case the key field should have been populated by the caller (e.g. in `install_path`).
-        config["key"] = config.get("key", uuid_string())
+        if config is not None:
+            config["key"] = config.get("key", uuid_string())
         info = info or ModelProbe.probe(model_path, config)
         override_key: Optional[str] = config.get("key") if config else None
 
@@ -546,7 +548,7 @@ class ModelInstallService(ModelInstallServiceBase):
         info.path = model_path.as_posix()
 
         # add 'main' specific fields
-        if hasattr(info, "config"):
+        if isinstance(info, CheckpointConfigBase):
             # make config relative to our root
             legacy_conf = (self.app_config.root_dir / self.app_config.legacy_conf_dir / info.config).resolve()
             info.config = legacy_conf.relative_to(self.app_config.root_dir).as_posix()

invokeai/backend/model_manager/config.py

@@ -135,7 +135,6 @@ class ModelConfigBase(BaseModel):
     )  # if model is converted or otherwise modified, this will hold updated hash
     description: Optional[str] = Field(description="human readable description of the model", default=None)
     source: Optional[str] = Field(description="model original source (path, URL or repo_id)", default=None)
-    last_modified: Optional[float] = Field(description="timestamp for modification time", default_factory=time.time)
 
     @staticmethod
     def json_schema_extra(schema: dict[str, Any], model_class: Type[BaseModel]) -> None:
@@ -160,6 +159,9 @@ class CheckpointConfigBase(ModelConfigBase):
 
     format: Literal[ModelFormat.Checkpoint] = ModelFormat.Checkpoint
     config: str = Field(description="path to the checkpoint model config file")
+    last_modified: Optional[float] = Field(
+        description="When this model was last converted to diffusers", default_factory=time.time
+    )
 
 
 class DiffusersConfigBase(ModelConfigBase):
@@ -191,7 +193,7 @@ class LoRADiffusersConfig(ModelConfigBase):
         return Tag(f"{ModelType.Lora}.{ModelFormat.Diffusers}")
 
 
-class VaeCheckpointConfig(ModelConfigBase):
+class VaeCheckpointConfig(CheckpointConfigBase):
     """Model config for standalone VAE models."""
 
     type: Literal[ModelType.Vae] = ModelType.Vae
@@ -257,25 +259,20 @@ class TextualInversionFolderConfig(ModelConfigBase):
         return Tag(f"{ModelType.TextualInversion}.{ModelFormat.EmbeddingFolder}")
 
 
-class _MainConfig(ModelConfigBase):
+class MainCheckpointConfig(CheckpointConfigBase):
-    """Model config for main models."""
-
-    variant: ModelVariantType = ModelVariantType.Normal
-    prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
-    upcast_attention: bool = False
-
-
-class MainCheckpointConfig(CheckpointConfigBase, _MainConfig):
     """Model config for main checkpoint models."""
 
     type: Literal[ModelType.Main] = ModelType.Main
+    variant: ModelVariantType = ModelVariantType.Normal
+    prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
+    upcast_attention: bool = False
 
     @staticmethod
     def get_tag() -> Tag:
         return Tag(f"{ModelType.Main}.{ModelFormat.Checkpoint}")
 
 
-class MainDiffusersConfig(DiffusersConfigBase, _MainConfig):
+class MainDiffusersConfig(DiffusersConfigBase):
     """Model config for main diffusers models."""
 
     type: Literal[ModelType.Main] = ModelType.Main
@@ -382,6 +379,6 @@ class ModelConfigFactory(object):
         assert model is not None
         if key:
             model.key = key
-        if timestamp:
+        if isinstance(model, CheckpointConfigBase) and timestamp is not None:
             model.last_modified = timestamp
         return model  # type: ignore

invokeai/backend/model_manager/load/model_loaders/controlnet.py

@@ -25,7 +25,7 @@ class ControlNetLoader(GenericDiffusersLoader):
     """Class to load ControlNet models."""
 
     def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
-        if config.format != ModelFormat.Checkpoint:
+        if not isinstance(config, CheckpointConfigBase):
             return False
         elif (
             dest_path.exists()

invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py

@@ -17,7 +17,7 @@ from invokeai.backend.model_manager import (
     ModelVariantType,
     SubModelType,
 )
-from invokeai.backend.model_manager.config import MainCheckpointConfig
+from invokeai.backend.model_manager.config import CheckpointConfigBase, MainCheckpointConfig
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ckpt_to_diffusers
 
 from .. import ModelLoaderRegistry
@@ -55,7 +55,7 @@ class StableDiffusionDiffusersModel(GenericDiffusersLoader):
         return result
 
     def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
-        if config.format != ModelFormat.Checkpoint:
+        if not isinstance(config, CheckpointConfigBase):
             return False
         elif (
             dest_path.exists()